A general strategy for reducing the variability in response-adaptive designs

Adaptive designs for clinical trials address the ethical requirement of allocating fewer patients to the inferior treatment as the trial progresses. We present here a generic strategy partly motivated by play-the-winner heuristic for reducing the variability of such designs. It is shown through simulations from a real clinical setting that employing this strategy improves the safety and the performance of some standard response adaptive designs. A closely related alternate strategy amenable to a theoretical analysis is also proposed with the same objective of lower variability.

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Publication Details

Journal
Communication in Statistics- Theory and Methods
Published
2024-10-20
DOI
https://doi.org/10.1080/03610926.2024.2408576
Primary Topic
Advanced Multi-Objective Optimization Algorithms
Type
article
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article

A general strategy for reducing the variability in response-adaptive designs

L. Ramprasath, Mohammed Shahid Abdulla
Communication in Statistics- Theory and Methods
Advanced Multi-Objective Optimization Algorithms
article

A general strategy for reducing the variability in response-adaptive designs

L. Ramprasath, Mohammed Shahid Abdulla
article en

Abstract

Adaptive designs for clinical trials address the ethical requirement of allocating fewer patients to the inferior treatment as the trial progresses. We present here a generic strategy partly motivated by play-the-winner heuristic for reducing the variability of such designs. It is shown through simulations from a real clinical setting that employing this strategy improves the safety and the performance of some standard response adaptive designs. A closely related alternate strategy amenable to a theoretical analysis is also proposed with the same objective of lower variability.

Communication in Statistics- Theory and MethodsVol. 54(13)
Indian Institute of Management Kozhikode (IN), Indian Institute of Management Ahmedabad (IN), Indian Institute of Management Bangalore (IN)
Openalex Percentile: Top 78%
Advanced Multi-Objective Optimization Algorithms
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